image-gen
Skill82 starsChanged 8 months agoMITView on GitHub
Generate AI images from text prompts. Triggers on: "生成图片", "画一张", "AI图", "generate image", "配图", "create picture", "draw", "visualize", "generate an image".
49 other projects use a version of this.
Adopted by
Most recently taken up by
- lohi-ai/babysittheir own version, first seen Nov 8, 2026
- uprinter/ai-agents-teamtheir own version, first seen Nov 8, 2026
- artemmarketolog/image-gentheir own version, first seen Nov 8, 2026
- ITch8/customs-data-skillstheir own version, first seen Nov 8, 2026
- dotslashsimran/simcrafttheir own version, first seen Nov 8, 2026
- notque/vexjoy-agenttheir own version, first seen Nov 7, 2026
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Other versions49 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 49
- ethereum/ethereum-org-website★ 6ksame name
- fastclaw-ai/fastclaw★ 1.4ksame name
- QuixiAI/agi-memory★ 623same name
- QuixiAI/Hexis★ 623same name
- notque/claude-code-toolkit★ 448same name
- notque/vexjoy-agent★ 448same name
- suitedaces/dorabot★ 247same name
- Sma1lboy/rove★ 184same name
- wpsnote/wpsnote-skills★ 184same name
- microsoft/Huabu★ 170same name
39 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
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The file
Show its rules and text
We split this skill into the rules it gives an agent
18 rules. 0 are common, 6 are distinctive, and 12 are very specific to this project.
0
Common
Most of the 35 edited versions we read keep these.
6
Distinctive
This author's own choices. Worth a look.
12
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 35
Always check CLI auth following shared/cli-authentication.md
- Very specific: line 36
Follow shared/cli-patterns.md for command execution and error handling
- Very specific: line 37
Always read config following shared/config-pattern.md before any interaction
- Very specific: line 46
Follow shared/cli-authentication.md § Auth Check.
- Very specific: line 58
All subsequent CLI calls use $CMD_PREFIX instead of hardcoded listenhub image.
- Very specific: line 62
Follow shared/config-pattern.md Step 0 (Zero-Question Boot).
- Distinctive: line 82
Only run when the user explicitly asks to reconfigure.
- Very specific: line 90
outputMode: Follow shared/output-mode.md § Setup Flow Question.
- Distinctive: line 107
If the prompt is very short (< 10 words) and the user hasn't asked for verbatim generation, offer to help enrich the prompt.
- Distinctive: line 122
Ask both together (independent parameters):
- Very specific: line 141
If flash model was selected, also offer: 1:4 (narrow portrait), 4:1 (wide landscape), 1:8 (extreme portrait), 8:1 (panoramic)
- Distinctive: line 176
Wait for explicit confirmation before running the CLI command.
- Very specific: line 182
Execute: Run the command with run_in_background: true and timeout: 180000:
- Very specific: line 194
If reference images were provided, add --reference for each:
- Very specific: line 211
Read OUTPUT_MODE from config.
- Very specific: line 255
Ask: "Would you like help enriching the prompt with style/lighting/composition details?"
- Distinctive: line 265
Always use English keywords (models trained on English)
- Distinctive: line 308
Ask prompt → "a serene mountain lake at dawn"
“Common” is measured: kept by at least 6 in 10 of the 35 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
When to Use
- User wants to generate an AI image from a text description
- User says "generate image", "draw", "create picture", "配图"
- User says "生成图片", "画一张", "AI图"
- User needs a cover image, illustration, or concept art
When NOT to Use
- User wants to create audio content (use
/podcast,/speech) - User wants to create a video (use
/explainer) - User wants to edit an existing image (not supported)
- User wants to extract content from a URL (use
/content-parser)
Purpose
Generate AI images using the ListenHub CLI. Supports text prompts with optional reference images (local files or URLs), multiple resolutions, and aspect ratios. Images are saved as local files.
Hard Constraints
- Always check CLI auth following
shared/cli-authentication.md - Follow
shared/cli-patterns.mdfor command execution and error handling - Always read config following
shared/config-pattern.mdbefore any interaction - Output saved to
.listenhub/image-gen/YYYY-MM-DD-{jobId}/— never~/Downloads/
<HARD-GATE>
Use the AskUserQuestion tool for every multiple-choice step — do NOT print options as plain text. Ask one question at a time. Wait for the user's answer before proceeding to the next step. After all parameters are collected, summarize the choices and ask the user to confirm. Do NOT call the image generation command until the user has explicitly confirmed.
</HARD-GATE>Step -1: CLI Auth Check
Follow shared/cli-authentication.md § Auth Check. If CLI is not installed or not logged in, auto-install and auto-login — never ask the user to run commands manually.
Then follow shared/cli-authentication.md § Auth Mode Detection to determine AUTH_MODE and set:
if [ "$AUTH_MODE" = "openapi" ]; then
CMD_PREFIX="listenhub openapi image"
else
CMD_PREFIX="listenhub image"
fiAll subsequent CLI calls use $CMD_PREFIX instead of hardcoded listenhub image.
Step 0: Config Setup
Follow shared/config-pattern.md Step 0 (Zero-Question Boot).
If file doesn't exist — silently create with defaults and proceed:
mkdir -p ".listenhub/image-gen"
echo '{"outputDir":".listenhub","outputMode":"inline"}' > ".listenhub/image-gen/config.json"
CONFIG_PATH=".listenhub/image-gen/config.json"
CONFIG=$(cat "$CONFIG_PATH")Do NOT ask any setup questions. Proceed directly to the Interaction Flow.
If file exists — read config silently and proceed:
CONFIG_PATH=".listenhub/image-gen/config.json"
[ ! -f "$CONFIG_PATH" ] && CONFIG_PATH="$HOME/.listenhub/image-gen/config.json"
CONFIG=$(cat "$CONFIG_PATH")Setup Flow (user-initiated reconfigure only)
Only run when the user explicitly asks to reconfigure. Display current settings:
当前配置 (image-gen):
输出方式:{inline / download / both}Then ask:
- outputMode: Follow
shared/output-mode.md§ Setup Flow Question.
Save immediately:
NEW_CONFIG=$(echo "$CONFIG" | jq --arg m "$OUTPUT_MODE" '. + {"outputMode": $m}')
echo "$NEW_CONFIG" > "$CONFIG_PATH"
CONFIG=$(cat "$CONFIG_PATH")Interaction Flow
Step 1: Image Description
Free text input. Ask the user:
Describe the image you want to generate.
If the prompt is very short (< 10 words) and the user hasn't asked for verbatim generation, offer to help enrich the prompt. Otherwise, use as-is.
Step 2: Model
Ask:
Question: "Which model?"
Options:
- "pro (recommended)" — gemini-3-pro-image, higher quality
- "flash" — gemini-3.1-flash-image, faster and cheaper, unlocks extreme aspect ratios (1:4, 4:1, 1:8, 8:1)Step 3: Resolution and Aspect Ratio
Ask both together (independent parameters):
Question: "What resolution?"
Options:
- "1K" — Standard quality
- "2K (recommended)" — High quality, good balance
- "4K" — Ultra high quality, slower generationQuestion: "What aspect ratio?"
Options (all models):
- "16:9" — Landscape, widescreen
- "1:1" — Square
- "9:16" — Portrait, phone screen
- "Other" — 2:3, 3:2, 3:4, 4:3, 21:9If flash model was selected, also offer: 1:4 (narrow portrait), 4:1 (wide landscape), 1:8 (extreme portrait), 8:1 (panoramic)
Step 4: Reference Images (optional)
Question: "Any reference images for style guidance?"
Options:
- "Yes" — Provide file paths or URLs
- "No references" — Generate from prompt onlyIf yes: Collect reference image paths or URLs (comma-separated). The CLI handles both local files and URLs natively — no need to distinguish between them.
- Max 5 references
- Supported formats: jpg, png, webp, gif
- Max 10MB per file
Each reference will be passed as a --reference flag to the CLI.
Step 5: Confirm & Generate
Summarize all choices:
Ready to generate image:
Prompt: {prompt text}
Model: {pro / flash}
Resolution: {1K / 2K / 4K}
Aspect ratio: {ratio}
References: {yes — N image(s) / no}
Proceed?Wait for explicit confirmation before running the CLI command.
Workflow
- Build CLI command: Construct the
$CMD_PREFIX createcommand with all collected parameters. Execute: Run the command with
run_in_background: trueandtimeout: 180000:$CMD_PREFIX create \ --prompt "{description}" \ --model "{model}" \ --lang "{lang}" \ --aspect-ratio {16:9|9:16|1:1} \ --size {1K|2K|4K} \ --jsonIf reference images were provided, add
--referencefor each:$CMD_PREFIX create \ --prompt "{description}" \ --model "{model}" \ --lang "{lang}" \ --aspect-ratio 16:9 \ --size 2K \ --reference ./sketch.png \ --reference ./photo.jpg \ --jsonThe
--langflag provides a language hint for the prompt. Detect from the user's prompt language (e.g., Chinese prompt →zh, English prompt →en).Parse result and present
Read
OUTPUT_MODEfrom config. Followshared/output-mode.mdfor behavior.Parse the CLI JSON output to extract the image URL:
IMAGE_URL=$(echo "$RESULT" | jq -r '.imageUrl')inlineorboth: Download to a temp file, then use the Read tool.JOB_ID=$(date +%s) listenhub download "$IMAGE_URL" -o /tmp/image-gen-${JOB_ID}.jpgThen use the Read tool on
/tmp/image-gen-{jobId}.jpg. The image displays inline in the conversation.Present:
图片已生成!downloadorboth: Save to the artifact directory.JOB_ID=$(date +%s) DATE=$(date +%Y-%m-%d) JOB_DIR=".listenhub/image-gen/${DATE}-${JOB_ID}" mkdir -p "$JOB_DIR" listenhub download "$IMAGE_URL" -o "${JOB_DIR}/${JOB_ID}.jpg"Present:
图片已生成! 已保存到 .listenhub/image-gen/{YYYY-MM-DD}-{jobId}/: {jobId}.jpg
Prompt Handling
Default: Pass the user's prompt directly without modification.
When to offer optimization:
- Prompt is very short (a few words) AND user hasn't requested verbatim
- Ask: "Would you like help enriching the prompt with style/lighting/composition details?"
When to never modify:
- Long, detailed, or structured prompts — treat the user as experienced
- User says "use this prompt exactly"
Optimization techniques (if user agrees):
- Style: "cyberpunk" → add "neon lights, futuristic, dystopian"
- Scene: time of day, lighting, weather
- Quality: "highly detailed", "8K quality", "cinematic composition"
- Always use English keywords (models trained on English)
- Show optimized prompt before submitting
API Reference
- CLI authentication:
shared/cli-authentication.md - CLI execution patterns:
shared/cli-patterns.md - Config pattern:
shared/config-pattern.md - Output mode:
shared/output-mode.md
Composability
- Invokes: nothing (direct CLI call)
- Invoked by: platform skills for cover images (Phase 2)
Example
User: "Generate an image: cyberpunk city at night"
Agent workflow:
- Prompt is short → offer enrichment → user declines
- Ask model → "pro"
- Ask resolution → "2K"
- Ask ratio → "16:9"
- No references
$CMD_PREFIX create \
--prompt "cyberpunk city at night" \
--model "gemini-3-pro-image" \
--lang en \
--aspect-ratio 16:9 \
--size 2K \
--jsonParse CLI JSON output per outputMode (see shared/output-mode.md).
Example 2 — With Reference Images
User: "Generate an image in this style" (provides local files and a URL)
Agent workflow:
- Ask prompt → "a serene mountain lake at dawn"
- Ask model → "pro"
- Ask resolution → "2K"
- Ask ratio → "16:9"
- References →
/path/to/style-reference.png,https://example.com/photo.jpg
$CMD_PREFIX create \
--prompt "a serene mountain lake at dawn" \
--model "gemini-3-pro-image" \
--lang en \
--aspect-ratio 16:9 \
--size 2K \
--reference /path/to/style-reference.png \
--reference https://example.com/photo.jpg \
--jsonParse CLI JSON output per outputMode (see shared/output-mode.md).
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